Research Article
Virtual Small Cell Selection Schemes Based on Sum Rate Analysis in Ultra-Dense Network
@ARTICLE{10.4108/eai.21-12-2017.153507, author={Qi Zhang and Jie Zeng and Xin Su and Liping Rong and Xibin Xu}, title={Virtual Small Cell Selection Schemes Based on Sum Rate Analysis in Ultra-Dense Network}, journal={EAI Endorsed Transactions on Future Internet}, volume={4}, number={12}, publisher={EAI}, journal_a={UE}, year={2017}, month={12}, keywords={Ultra-dense network, virtual small cell, sum rate, pattern search.}, doi={10.4108/eai.21-12-2017.153507} }
- Qi Zhang
Jie Zeng
Xin Su
Liping Rong
Xibin Xu
Year: 2017
Virtual Small Cell Selection Schemes Based on Sum Rate Analysis in Ultra-Dense Network
UE
EAI
DOI: 10.4108/eai.21-12-2017.153507
Abstract
Ultra-Dense Network (UDN) is regarded as a major development trend in the evolution of future networks, due to its ability to provide larger sum rate to the whole system and meet higher users' Quality of Service (QoS). Different from the existing heterogeneous network, UDN has a smaller cell radius and a new network structure. The core concept of UDN is to deploy the low power Base Stations (BSs), i.e. Virtual Small Cells (VSCs). First, we derive an ergodic sum rate expression. To acquire the maximum ergodic sum rate of all the users, then we adopt the selection mode based on minimum distance. Due to the consideration of the computation complexity of the above VSC selection scheme, we finally propose a novel VSC selection scheme based on pattern search. The simulation results demonstrate the correctness of the ergodic sum rate expression and show the lower computation complexity of the proposed VSC selection scheme comparing with the above reference scheme.
Copyright © 2017 Qi Zhang et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.